Existing computational models of dopamine's role in reinforcement learning are now quite well developed. These models make specific predictions about how changes in the firing rates of midbrain dopamine neurons should change the values subjects place on actions. While previous single neuron recording studies have largely validated these computational models, there have been very few efforts to use direct electrical manipulations of these neurons to examine these theories. This is of particular relevance because electrical manipulations of deep brain nuclei are now being used to treat a number of psychiatric disorders - including drug addiction. In this proposal, we describe a series of experiments aimed at testing the hypothesis that if the firing rates of midbrain dopamine neurons are manipulated with sub-second precision in a manner specified by existing computational theories, this may profoundly regulate behavioral preferences in a highly precise way. If this is the case, this finding would suggest a series of translationally-relevant experiments on the effects of deep brain stimulation on drug addiction. The current proposal seeks to lay the theoretical and experimental foundations for such experiments in the future.